Endocrinology

Menopause

Latest AI and machine learning research in menopause for healthcare professionals.

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Classification of non-TCGA cancer samples to TCGA molecular subtypes using compact feature sets.

Molecular subtypes, such as defined by The Cancer Genome Atlas (TCGA), delineate a cancer's underlyi...

Non-invasive blood glucose monitoring using PPG signals with various deep learning models and implementation using TinyML.

Accurate and continuous blood glucose monitoring is essential for effective diabetes management, yet...

Gait-based Parkinson's disease diagnosis and severity classification using force sensors and machine learning.

A dual-stage model for classifying Parkinson's disease severity, through a detailed analysis of Gait...

π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing.

Peptide sequencing via tandem mass spectrometry (MS/MS) is essential in proteomics. Unlike tradition...

Multi-Modal Federated Learning for Cancer Staging Over Non-IID Datasets With Unbalanced Modalities.

The use of machine learning (ML) for cancer staging through medical image analysis has gained substa...

Unsupervised Non-Rigid Histological Image Registration Guided by Keypoint Correspondences Based on Learnable Deep Features With Iterative Training.

Histological image registration is a fundamental task in histological image analysis. It is challeng...

Semantic prioritization in visual counterfactual explanations with weighted segmentation and auto-adaptive region selection.

In the domain of non-generative visual counterfactual explanations (CE), traditional techniques freq...

Non-Invasive Diagnosis of Moyamoya Disease Using Serum Metabolic Fingerprints and Machine Learning.

Moyamoya disease (MMD) is a progressive cerebrovascular disorder that increases the risk of intracra...

NATE: Non-pArameTric approach for Explainable credit scoring on imbalanced class.

Credit scoring models play a crucial role for financial institutions in evaluating borrower risk and...

Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients.

BACKGROUND AND OBJECTIVE: Helmet-Continuous Positive Airway Pressure (H-CPAP) is a non-invasive resp...

Machine learning algorithms in constructing prediction models for assisted reproductive technology (ART) related live birth outcomes.

Currently applicable models for predicting live birth outcomes in patients who received assisted rep...

Radiomics for differentiating adenocarcinoma and squamous cell carcinoma in non-small cell lung cancer beyond nodule morphology in chest CT.

Distinguishing between primary adenocarcinoma (AC) and squamous cell carcinoma (SCC) within non-smal...

Generation of deep learning based virtual non-contrast CT using dual-layer dual-energy CT and its application to planning CT for radiotherapy.

This paper presents a novel approach for generating virtual non-contrast planning computed tomograph...

Machine learning-based prediction of non-aeration linear alkylbenzene sulfonate mineralization in an oxygenic microalgal-bacteria biofilm.

Microalgal-bacteria biofilm shows great potential in low-cost greywater treatment. Accurately predic...

The aluminum standard: using generative Artificial Intelligence tools to synthesize and annotate non-structured patient data.

BACKGROUND: Medical narratives are fundamental to the correct identification of a patient's health c...

Bias in machine learning applications to address non-communicable diseases at a population-level: a scoping review.

BACKGROUND: Machine learning (ML) is increasingly used in population and public health to support ep...

Predicting lncRNA-protein interactions using a hybrid deep learning model with dinucleotide-codon fusion feature encoding.

Long non-coding RNAs (lncRNAs) play crucial roles in numerous biological processes and are involved ...

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